Journal ArticleDOI
Multi-key privacy-preserving deep learning in cloud computing
TLDR
This work presents a basic scheme based on multi-key fully homomorphic encryption (MK-FHE), and proposes a hybrid structure scheme by combining the double decryption mechanism and FHE, and proves that these two multi- key privacy-preserving deep learning schemes over encrypted data are secure.About:
This article is published in Future Generation Computer Systems.The article was published on 2017-09-01. It has received 386 citations till now. The article focuses on the topics: Encryption & Homomorphic encryption.read more
Citations
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Journal ArticleDOI
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
Wei Yang Bryan Lim,Nguyen Cong Luong,Dinh Thai Hoang,Yutao Jiao,Ying-Chang Liang,Qiang Yang,Dusit Niyato,Chunyan Miao +7 more
TL;DR: The concept of federated learning (FL) as mentioned in this paperederated learning has been proposed to enable collaborative training of an ML model and also enable DL for mobile edge network optimization in large-scale and complex mobile edge networks, where heterogeneous devices with varying constraints are involved.
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Federated Learning in Mobile Edge Networks: A Comprehensive Survey
Wei Yang Bryan Lim,Nguyen Cong Luong,Dinh Thai Hoang,Yutao Jiao,Ying-Chang Liang,Qiang Yang,Dusit Niyato,Chunyan Miao +7 more
TL;DR: In a large-scale and complex mobile edge network, heterogeneous devices with varying constraints are involved, this raises challenges of communication costs, resource allocation, and privacy and security in the implementation of FL at scale.
Journal ArticleDOI
Significant Permission Identification for Machine-Learning-Based Android Malware Detection
TL;DR: Significant Permission IDentification (SigPID), a malware detection system based on permission usage analysis to cope with the rapid increase in the number of Android malware, is introduced.
Journal ArticleDOI
A Survey of Deep Learning: Platforms, Applications and Emerging Research Trends
William G. Hatcher,Wei Yu +1 more
TL;DR: A thorough investigation of deep learning in its applications and mechanisms is sought, as a categorical collection of state of the art in deep learning research, to provide a broad reference for those seeking a primer on deep learning and its various implementations, platforms, algorithms, and uses in a variety of smart-world systems.
Journal ArticleDOI
Secure attribute-based data sharing for resource-limited users in cloud computing
TL;DR: This paper proposes a new attribute-based data sharing scheme suitable for resource-limited mobile users in cloud computing and is proven secure against adaptively chosen-ciphertext attacks, which is widely recognized as a standard security notion.
References
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Journal ArticleDOI
Reducing the Dimensionality of Data with Neural Networks
TL;DR: In this article, an effective way of initializing the weights that allows deep autoencoder networks to learn low-dimensional codes that work much better than principal components analysis as a tool to reduce the dimensionality of data is described.
Journal ArticleDOI
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
Geoffrey E. Hinton,Li Deng,Dong Yu,George E. Dahl,Abdelrahman Mohamed,Navdeep Jaitly,Andrew W. Senior,Vincent Vanhoucke,Patrick Nguyen,Tara N. Sainath,Brian Kingsbury +10 more
TL;DR: This article provides an overview of progress and represents the shared views of four research groups that have had recent successes in using DNNs for acoustic modeling in speech recognition.
Proceedings ArticleDOI
Speech recognition with deep recurrent neural networks
TL;DR: This paper investigates deep recurrent neural networks, which combine the multiple levels of representation that have proved so effective in deep networks with the flexible use of long range context that empowers RNNs.
Proceedings ArticleDOI
Fully homomorphic encryption using ideal lattices
TL;DR: This work proposes a fully homomorphic encryption scheme that allows one to evaluate circuits over encrypted data without being able to decrypt, and describes a public key encryption scheme using ideal lattices that is almost bootstrappable.
Posted Content
Speech Recognition with Deep Recurrent Neural Networks
TL;DR: In this paper, deep recurrent neural networks (RNNs) are used to combine the multiple levels of representation that have proved so effective in deep networks with the flexible use of long range context that empowers RNNs.